Cargando…
Research on Fatigued-Driving Detection Method by Integrating Lightweight YOLOv5s and Facial 3D Keypoints
In response to the problem of high computational and parameter requirements of fatigued-driving detection models, as well as weak facial-feature keypoint extraction capability, this paper proposes a lightweight and real-time fatigued-driving detection model based on an improved YOLOv5s and Attention...
Autores principales: | Ran, Xiansheng, He, Shuai, Li, Rui |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10575209/ https://www.ncbi.nlm.nih.gov/pubmed/37837095 http://dx.doi.org/10.3390/s23198267 |
Ejemplares similares
-
Pedestrian detection algorithm integrating large kernel attention and YOLOV5 lightweight model
por: Yin, Yuping, et al.
Publicado: (2023) -
YOLOv5-AC: Attention Mechanism-Based Lightweight YOLOv5 for Track Pedestrian Detection
por: Lv, Haohui, et al.
Publicado: (2022) -
Research and Implementation of Millet Ear Detection Method Based on Lightweight YOLOv5
por: Qiu, Shujin, et al.
Publicado: (2023) -
STMS-YOLOv5: A Lightweight Algorithm for Gear Surface Defect Detection
por: Yan, Rui, et al.
Publicado: (2023) -
A Lightweight YOLOv5-MNE Algorithm for SAR Ship Detection
por: Pang, Lei, et al.
Publicado: (2022)